Several immune cells, e.g. B cells or T cells, infiltrate various types of tumors and are known to have an effect on the further tumor development. The capability to escape destruction by an immune cell is meanwhile considered as an important hallmark of many cancer types. The effect of the immune cells may depend on the cancer type. The type of the infiltrating immune cells, for example, T-cells, B-cells or macrophages and the degree of infiltration may have an impact on tumor progression. Thus context-specific information relating to the infiltration of tumor tissue with immune cells may be used for making a prognosis of the tumor development for a particular patient.
Typically, in immune score computations, the scientist uses a multiplex assay that involves staining one piece of tissue or a simplex assay that involves staining adjacent serial tissue sections to detect or quantify, for example, multiple proteins or nucleic acids etc. in the same tissue block. With the stained slides available, the immunological data, can be estimated from the tumor tissue samples. It has been reported that this data can be used to predict the patient survival of colorectal cancer and demonstrates important prognostic role. In both the microscopy slide interpretation process and the digital pathology workflow, the expert reader reviews the slide under a microscope. The expert reader may read the image of a slide, which has been scanned or digitized, from a monitor in order to make a prediction of further tumor development. However, such a manual, subjective assessment of the prognosis given a particular infiltration pattern of the tumors of a slide is not reproducible. Rather, it is highly subjective and biased to the readers. As a consequence, tumor progress predictions based on a manual inspection of tumor cell slides tend to vary from pathologist to pathologist, and are not reproducible.
Also, many methods of computing an immune score do not consider activity of lymphocytes outside of the tumor. United States patent application 20140185891A1, entitled Generating Image-Based Diagnostic Tests By Optimizing Image Analysis and Data Mining Of Co-Registered Images, discloses an image-based test diagnostic tests that predicts a probability of recurrence of cancer utilizing heat maps generated from overlapping features in a combined image of adjacent tissue sections. However, the method appears applicable to cell counts in the tumor. Thus, the computations are limited to cellular activity or counts within an identified tumor region, and do not factor in the activity of cellular activity outside of the tumor region. United States patent application 20130203614A1, entitled Methods for Predicting the Survival time of a Patient Suffering from a Solid Cancer, discloses methods for the prognosis of survival time of a patient having colon cancer that appears to consider the invasive margin of the colon cancer tumor. However, the method disclosed in U.S. patent application 20130203614A1 is directed to cells that are known to be associated with colorectal cancer and does not appear to present a digital imaging methodology that promotes a methodology that generates a consistent prognosis.
All references, including any patents or patent applications cited in this specification are hereby incorporated by reference. No admission is made that any reference constitutes prior art or form part of the common general knowledge in the art.